AI-based tools that predict brain responses to video content have several important limitations.

These tools rely on models trained on existing neuroscience datasets. While they can provide useful predictions, they do not capture real-time brain activity from actual viewers watching the content. This means the results are estimates rather than direct measurements.

Additionally, these tools may not perform equally well across all types of content, audiences, or cultural contexts, since their training data has certain boundaries. They also cannot replace the depth of insight that comes from well-designed participant studies using brain scanning equipment.

Because of these limitations, many teams use AI prediction tools for early-stage testing and creative iteration, while still relying on traditional neuromarketing research for high-stakes decisions that require stronger validation.